逼近现实世界双目标覆盖问题的Pareto边界

IF 1.1 4区计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Infor Pub Date : 2022-04-08 DOI:10.1080/03155986.2022.2040274

Nils-Hassan Quttineh, Uledi Ngulo, T. Larsson

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引用次数: 0

摘要

摘要:本文研究了一个基于实际应用的双目标覆盖问题，该问题涉及大规模室外区域的摄像机监控系统的设计。在此应用程序中，监视整个区域的成本高得令人望而却步，因此有必要能够向决策者提供总成本和监视区域部分之间的权衡。这个问题可以被描述为一个有两个目标的集合覆盖问题，描述成本和覆盖约束的实现部分。寻找这些目标的帕累托边界是非常需要计算的，因此我们推导了一种在实际可行的计算时间内找到一个好的近似边界的方法。该方法是基于ϵ-constraint的重新表述，建立启发式的集合覆盖问题，和亚梯度优化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Approximating the Pareto frontier for a challenging real-world bi-objective covering problem

Abstract We study a bi-objective covering problem stemming from a real-world application concerning the design of camera surveillance systems for large-scale outdoor areas. It is in this application prohibitively costly to surveil the entire area, and therefore necessary to be able to present a decision-maker with trade-offs between total cost and the portion of the area that is surveilled. The problem can be stated as a set covering problem with two objectives, describing cost and portion of covering constraints that are fulfilled. Finding the Pareto frontier for these objectives is very computationally demanding and we therefore derive a method for finding a good approximate frontier in a practically feasible computing time. The method is based on the ϵ-constraint reformulation, an established heuristic for set covering problems, and subgradient optimization.

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来源期刊

Infor 管理科学-计算机：信息系统

CiteScore

2.60

自引率

7.70%

发文量

审稿时长

>12 weeks

期刊介绍： INFOR: Information Systems and Operational Research is published and sponsored by the Canadian Operational Research Society. It provides its readers with papers on a powerful combination of subjects: Information Systems and Operational Research. The importance of combining IS and OR in one journal is that both aim to expand quantitative scientific approaches to management. With this integration, the theory, methodology, and practice of OR and IS are thoroughly examined. INFOR is available in print and online.